LEAFS Assessment of Electricity Storage System and ... · Fabian Moisl 1, Wolfgang Prüggler2,Georg Lettner 1Technische Universität Wien, Energy Economics Group 2MOOSMOAR Energies

15th IAEE European Conference

3 - 6 September 2017

Vienna, Austria

Fabian Moisl1, Wolfgang Prüggler2,Georg Lettner1

1Technische Universität Wien, Energy Economics Group2MOOSMOAR Energies OG

[email protected]

LEAFS – Assessment of Electricity Storage

System and Flexible Loads in the

Distribution Grid

Table of contents

• Overview and Introduction

• Methodology

• Input data and assumptions

• Results

• Conclusions and outlook

4.9.2017 2

Overview

• Generic distribution network section consisting of 207 customers (private households

and small businesses).

• A private household may have distributed generation (PV system), a battery storage

system and/or flexible loads.

• Each household pursues a operation strategy for its storage systems and flexible

loads (e.g. minimize electricity procurement costs).

4.9.2017 3

Figure 1. Schematic representation of the distribution grid section. APA-Auftragsgrafik, Source: AIT

Method 1/3

• A household (prosumer) may have a PV system, a battery storage system, flexible

and inflexible load and pursues an operation strategy.

• Each operation strategy is represented by a linear optimization problem (min. costs):

4.9.2017 4

Figure 2. Schematic representation of a prosumer.

Method 2/3

General constraints of the optimization problem:

Constraints due to demand response of flexible loads (electric loads with thermal

storage such as refrigerators, freezers, water boilers, heat pumps, radiators):

4.9.2017 5

Operation strategy Parameters and constraints

Maximize self-consumption

Method 3/3 - Overview of different operation strategies

4.9.2017 6



Minimize electricity procurement

costs




costs

Minimize PV curtailment




costs

Minimize PV curtailment

Minimize procurement power

Input Data and Assumptions

• Household-load time series were generated by means of a load profile generator [1]

considering the household’s annual energy consumption.

• PV generation time series are based on historical time series.

4.9.2017 7

Parameter Value Unit

Electricity price (constant) 6.5 ct./kWh

Electricity price (time variable), EPEX

Spot Intraday Continuous DE/AT 2016

Ø 6.5 ct./kWh

Grid tariff kWh rate 5 ct./kWh

Grid tariff kW rate 40 EUR/(kW*a)

Taxes 3 ct./kWh

PV remuneration 4.5 ct./kWh

PV feed-in limit as fraction of the

installed capacity

70 %

Flexible electric load Deferral

period (h)

water boiler 12

heat pump 1

radiator 1

refrigerator 1

freezers 4

Table 2. Deferral periods of various

flexible electric loads according to [2].Table 3. Assumptions regarding electricity costs and tariffs.

Own presumptions based on [3].

Economic parameters for discounted cashflow analysis

• aDSM cost: 80 EUR/yr. (hardware + installation cost)

• Customer interest rate = 2%/yr; average inflation rate = 2%/yr

• Inverter change after 10 years (extra cost of 1 kEUR considered)

• Random variation of revenues (for each operation strategy (see next slides) as of changing PV

generation and consumption patterns) within 10% bandwidth

4.9.2017 8

Storage parameter (Fronius Battery Systems) Value Unit

Useable capacity (at DOD = 80%) 3.6 4.8 7 kWh

Customer price incl. space cost, installation, discounts, subsidies and

taxes (manufacturer's information)

8.3

(2.31)

9.4

(1.96)

11.7

(1.67)

kEUR

(kEUR/kWh)

Cycle lifetime 7000 cycles

calendric lifetime (= evaluation period) 20 years

Installation cost 1.5 kEUR

space cost 250 EUR/m2

Subsidy (based on nominal capacity) 400 EUR/kWh

Average storage operation cost [4] 2.2 EUR/(kWh*yr)

Taxes 20 %

customer discount 10 %

Results duration curves

4.9.2017 9

Figure 3. Duration curve of accumulated load flow at the substation of the distribution grid segment.

‚baseline‘ = no storage/ no flexible load; ‚max. self-consumption‘ = fixed kWh-based el. prices; ‚min. el. procurement

cost‘ = time variable end-user prices; ‚min. procurement power‘= 40 EUR/kW*yr. kW-based grid tariff.

0

50

100

150

200

250

3.6 kWh

Re

ve

nu

es

in

[€

/yr]

Storage and aDSM revenues at strategy: max. self

consumption

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920

DiscountedCashFlowin

[€/yr]

Yearofopera on

CashflowEberstalzell:RevenuesMAX

Willingnesstopay

DCFmicroeconomicview(225storagecycles/yr)

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on

CashflowEberstalzell:RevenuesMEDIAN

Willingnesstopay


-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on

CashflowEberstalzell:RevenuesMIN

Willingnesstopay


Results for operation strategy: max. self-consumption

4.9.2017 10

MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

Inverter change in

year 11

0

50

100

150

200

250

300

350

3.6 kWh

Re

ven

ue

s i

n [€

/yr]

Storage and aDSM revenues at strategy: min. el.

procurement cost

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920

DiscountedCashFlowin[€/yr]

Yearofopera on


Willingnesstopay


-€500

-€450

-€400

-€350

-€300

-€250

-€200

-€150

-€100

-€50

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


Results for operation strategy: min. electricity procurement

cost

4.9.2017 11

MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

Inverter change in

year 11

0

50

100

150

200

250

300

aDSM

Rev

en

ue

s in

[€

/yr]

aDSM revenues at strategy: min. el. procurement cost

-€100

-€50

€-

€50

€100

€150

€200

1234567891011121314151617181920


Yearofopera on


Willingnesstopay/Surplus

DCFmicroeconomicview

-€100

-€90

-€80

-€70

-€60

-€50

-€40

-€30

-€20

-€10

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


-€100

-€90

-€80

-€70

-€60

-€50

-€40

-€30

-€20

-€10

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


Results for operation strategy: min. electricity procurement

cost

4.9.2017 12

MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

0

50

100

150

200

250

300

350

400

450

3.6 kWh

Re

ven

ue

s i

n [€

/yr]

Storage and aDSM revenues at strategy: min. el.

procurement power

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


Yearofopera on


Willingnesstopay


-€400

-€350

-€300

-€250

-€200

-€150

-€100

-€50

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


Results for operation strategy: min. procurement power

4.9.2017 13

MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

0

50

100

150

200

250

300

aDSM

Rev

en

ue

s in

[€

/yr]

aDSM revenues at strategy: min. el. procurement power

-€100

-€50

€-

€50

€100

€150

€200

1234567891011121314151617181920


Yearofopera on


Willingnesstopay/Surplus


-€100

-€90

-€80

-€70

-€60

-€50

-€40

-€30

-€20

-€10

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


-€100

-€90

-€80

-€70

-€60

-€50

-€40

-€30

-€20

-€10

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


Results for operation strategy: min. procurement power

4.9.2017 14

MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

Conclusions and Outlook

Outlook

4.9.2017 15

• Fixed kWh-based end-user prices and tariffs

(OS. max. self-consumption) do not provide

incentives to operate a storage system/flexible

loads in a grid beneficial way (no reduction in

accumulated peak load or peak feed-in)

• Time variable end-user electricity prices

result in significantly higher peak loads (+80%)

at substations (high simultaneity).

• A reduction of the individual customers peak

load does not reduce the peak load at the

substation (due to lack of simultaneity).

• ‘Willingness to pay’ for battery storage

systems needed of about 200 – 500 EUR/yr.

• Comparison to bulk battery energy

storage system (100kWh).

• Voltage band consideration (power system

simulation)

• Possible increase in consumption due to a

shift from kWh-based to kW-based prices

was not considered but should be kept in mind

(energy efficiency).

Acknowledgements

This paper is based on the research project "LEAFS - Integration of Loads and

Electric Storage Systems into advanced Flexibility Schemes for LV Networks".

The project LEAFS is funded by the Austrian Climate and Energy Fund within

the programme Energieforschung 2014.

4.9.2017 16

References

4.9.2017 17

[1] W. Gawlik et al. „aDSM - Aktives Demand-Side-Management durch Einspeiseprognose“,

FFG‐Forschungsprojekt, NE2020, 5. AS, Projektnummer: 834612, Endbericht, Wien, April 2014.

[2] de Bruyn, K., Kollmann, A., Moser, S., Schmidthaler, M., Amann, C., Elbe, C., Schmautzer,

E., Kraussler, A., Reinofer-Gubisch, M., Pucker, J., et al. (2014). LoadShift: Lastverschiebung in

Haushalt, Industrie, Gewerbe und kommunaler Infrastruktur - Potenzialanalyse für Smart Grids (Linz

und Graz). Berichte aus Energie- und Umweltforschung

[3] E-Control Tariff calculator, https://www.e-control.at/konsumenten/service-und-

beratung/toolbox/tarifkalkulator , as consulted online on 26 April 2017.

[4] Leipziger Institut für Energie, „Wirtschaftlichkeit Batteriespeicher”, Kurzexpertise, Leipzig

2014

https://www.e-control.at/konsumenten/service-und-beratung/toolbox/tarifkalkulator

FABIAN MOISL

Technische Universität Wien

Institute of Energy Systems and Electrical Drives

Energy Economics Group – EEG

Gußhausstraße 25-29 / E370-3

1040 Vienna, Austria

[T] +43 1 58801 370373

[E] [email protected]

[W] www.eeg.tuwien.ac.at

Methodology:

Summing discounted cashflows over the lifetime/investment-period of a project.

0

1 )1(C

r

CNPV

n

tt

t

NPV Net Present Value [€]

n Lifefime/investment-period [y]

Ct Cash flow in year t [€]

r rate of return [1]

C0 Initial investment [€]

C0

t0 t

[€/y]

cash flows

cash receipts

cash payments

+

-

discounted CF

t1 t2 t3 t4

NPV

Discounted cash flow, Net present value (NPV)

0

100

200

300

400

500

600

700

800

3.6 kWh 4.8 kWh 7.2 kWh

Reven

ues in

[€/y

r]

Boxplot: Storage and aDSM revenues @ strategy max. self consumption

Appendix - Revenue parameters I

4.9.2017 20

Appendix - Revenue parameters II

4.9.2017 21

0

100

200

300

400

500

600

700

800

900

1000

3.6 kWh 4.8 kWh 7.2 kWh

Reven

ues

in

[€/y

r]

Boxplot: Storage and aDSM revenues @ min. el. procurement cost

Appendix - Revenue parameters III

4.9.2017 22

0

100

200

300

400

500

600

700

800

3.6 kWh 4.8 kWh 7.2 kWh

Reven

ues

in

[€/y

r]

Boxplot: Storage and aDSM revenues @ strategy min. el procurement power

0

50

100

150

200

250

3.6 kWh

Re

ve

nu

es

in

[€

/yr]


consumption

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920DiscountedCashFlowin

[€/yr]

Yearofopera on


Willingnesstopay


-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

0

50

100

150

200

250

3.6 kWh

Re

ve

nu

es

in

[€

/yr]


consumption

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on

Eberstalzell:RevenuesMAX@futurecost

Willingnesstopay


-€600

-€500

-€400

-€300

-€200

-€100

€-


[€/yr]

Yearofopera on

Eberstalzell:RevenuesMEDIAN@futurecost

Willingnesstopay


-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on

Eberstalzell:RevenuesMIN@futurecost

Willingnesstopay


MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

Future cost estimation:

LiIon cell prices decline

to 20% of current values

0

50

100

150

200

250

300

350

400

450

7.2 kWh

Re

ve

nu

es

in

[€

/yr]


consumption

-€800

-€700

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


-€800

-€700

-€600

-€500

-€400

-€300

-€200

-€100

€-


[€/yr]

Yearofopera on


Willingnesstopay


-€800

-€700

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on


Willingnesstopay


MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

0

50

100

150

200

250

300

350

400

450

7.2 kWh

Re

ve

nu

es

in

[€

/yr]


consumption

-€800

-€700

-€600

-€500

-€400

-€300

-€200

-€100

€-

€100

1234567891011121314151617181920


[€/yr]

Yearofopera on

Eberstalzell:RevenuesMAX@futurecost

Willingnesstopay


-€800

-€700

-€600

-€500

-€400

-€300

-€200

-€100

€-

€100


[€/yr]

Yearofopera on

Eberstalzell:RevenuesMEDIAN@futurecost

Willingnesstopay


-€800

-€700

-€600

-€500

-€400

-€300

-€200

-€100

€-

1234567891011121314151617181920


[€/yr]

Yearofopera on

Eberstalzell:RevenuesMIN@futurecost

Willingnesstopay


MIN

MAX

MEDIAN

Revenue bandwith:

[MAX; MAX*0.9]

Revenue bandwith:

[MED*1.1; MED*0.9]

Revenue bandwith:

[MIN*1.1; MIN]

Future cost estimation:

LiIon cell prices decline

to 20% of current values

-€600

-€500

-€400

-€300

-€200

-€100

€-

1 2 3 4 5 6 7 8 9 1011121314151617181920


Yearofopera on

Eberstalzell:4.8kWh_MEDIAN_incl.systemandmacroeconomiceffects

Willingnesstopay


DCFincl.grideffects

DCFincl.gridandmacroeconomiceffects

Evaluation outlook

4.9.2017 27

Documents

LEAFS Assessment of Electricity Storage System and ... · Fabian Moisl 1, Wolfgang Prüggler2,Georg Lettner 1Technische Universität Wien, Energy Economics Group 2MOOSMOAR Energies